Given a waveform, we truncate to 150k frames, and compute the log-Mel spectrogram. Spectrograms are z-scored using training statistics, which we found to be important for generalization. By default, we augment waveforms by selecting contiguous crops with a minimum and maximum ratio of 0.08 to 1.0, along with Gaussian noise with a scale of 1.0. We separately explore first computing the spectrogram, then applying a time and frequency mask as augmentation, denoted by the (\(^*\) ) superscript in Table REF . Regardless, we fit a ResNet50 [1]} to map the spectrogram to a 2048 dimensional embedding.
